gasearch - Genetic algorithm based hyperparameter tuner
gasearch - Finding hyperparameters the way nature intended
Hyperparameter search isn’t an exact science. We’ve all heard that one.
gasearch searches the parameter space using genetic algorithm, with multiple solutions in each generation competing for inclusion in the next.
Mutation of the existing solutions introduces new characteristics and crossover helps the beneficial traits spread across the population. At the same time, proportional selection prevents early convergence of algorithm on local minimum, keeping the population diverse and dynamic.
However, since genetic algorithms are heuristic, there can not be any guarantee that the solution delivered is the optimal one for a given problem. Regardless of the number of iterations.
The package follows scikit-learn API conventions and can be readily integrated with existing pipelines.
- TODO:
Implement alternative selection algorithms
Publish more examples
Implement alternative crossover operations
Improve docs
Optimize, optimize, optimize …
1 maintainer
Release files for gasearch 0.0.7
For a detailed explanation of source distributions (sdists) and built distributions (wheels), please see the package formats documentation.
Source distribution (sdist)
| File | Size | Uploaded | |
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| gasearch-0.0.7.tar.gz | 11.8 kB | Details |
Built distribution (wheel)
| File | Interpreter | ABI | Platform | Reset |
|---|---|---|---|---|
| gasearch-0.0.7-py3-none-any.whl | Python 3 | none | any | Details |
Total release size: 23.2 kB
Release files / gasearch-0.0.7.tar.gz
| Download URL | gasearch-0.0.7.tar.gz |
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| Size | 11.8 kB |
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Release files / gasearch-0.0.7-py3-none-any.whl
| Download URL | gasearch-0.0.7-py3-none-any.whl |
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| Size | 11.4 kB |
| Tags | Python 3 |
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